Knowledge that Transforms

This paper reports evidence that OECD economies adopting fixed exchange rates in the process of forming the European currency union experienced declines in labor share of income at the industry level. This occurs most sharply among countries that experienced the biggest changes in their exchange rate policy. An implication of New Keynesian sticky price theory is that monetary policy has a first-order impact on labor share through the interaction of business cycle uncertainty and the choice of optimal markups. However, there is also evidence that goods market integration encouraged by the euro had a negative impact on the bargaining position of labor.

It is well known that augmenting a standard linear regression model with variables that are correlated with the error term but uncorrelated with the original regressors will increase the asymptotic efficiency of the original coefficients. We argue that in the context of predicting excess returns, valid augmenting variables exist and are likely to yield substantial gains in estimation efficiency and, hence, predictive accuracy. The proposed augmenting variables are ex post measures of an unforecastable component of excess returns: ex post errors from macroeconomic survey forecasts, the surprise components of asset price movements around macroeconomic news announcements, or even the weather. These “surprises” cannot be used directly in forecasting—they are not observed at the time that the forecast is made—but can nonetheless improve forecasting accuracy by reducing parameter estimation uncertainty. We derive formal results about the benefits and limits of this approach and apply it to standard examples of forecasting excess bond and equity returns. We find substantial improvements in out-of-sample forecast accuracy for standard excess bond return regressions; gains for forecasting excess stock returns are much smaller.

It is shown that in a nonparametric nonseparable triangular system, the conditional moment restriction (CMR) does not identify the average structural function (ASF). The CMR identifies the ASF only if the model is structurally separable in observable covariates and unobservable random errors. This excludes, for instance, random coefficient models in which the CMR in general does not identify the average response. An implication of our results is that empirical researchers should use methods other than CMR if they want to estimate the average response in models that are not additively separable.

We consider a dynamic stochastic general equilibrium model (DSGE) in which firms follow one of four price‐setting regimes: sticky prices, sticky information, rule of thumb, or full‐information flexible prices. The parameters of the model, including the fraction of each type of firm, are estimated by matching the moments of the observed variables of the model to those found in the data. We find that sticky price firms and sticky information firms jointly account for over 80% of firms in the model. We compare the performance of our hybrid model to pure sticky price and sticky information models along various dimensions, including monetary policy implications.

Most studies of comparative productivities fail to find evidence of convergence in OECD manufacturing despite major economic growth theories predicting convergence. Using manufacturing data for nineteen OECD countries over the period from 1870 to 2006, this study finds strong evidence of unconditional β-convergence as well as σ-convergence. Panel data estimates suggest that the convergence has been driven by domestic R&D, international R&D spillovers, and financial development as predicted by Schumpeterian growth theories.

We study the impact of misreported treatment status on the estimation of causal treatment effects, focusing on applications where no additional information or repeated measurements are available. We first characterize the bias introduced by misclassification on the average treatment effect on the treated (ATT) under a conditional independence assumption, in both a binary and a multiple-treatment setting. We find that the bias of matching-type estimators computed from misclassified data cannot in general be signed. We subsequently provide easily implementable methods to bound the ATT of interest semiparametrically, in particular allowing for very general forms of impact heterogeneity and of the no-treatment outcome equations, as well as for some dependence of the misreporting probabilities on individual characteristics. The empirical problem that motivates our paper is the estimation of the wage returns to a number of educational qualifications in the United Kingdom, allowing for misreporting in attainment. We investigate the sensitivity of the raw estimates to the presence of misclassification and explore the identification power of plausible restrictions on the nature and extent of misclassification. We show that the resulting bounds are sometimes wide but generally point to reasonable ranges of positive values for average returns to schooling among the schooled. For the range of educational qualifications considered, we further show that the claim sometimes made that measurement error bias roughly cancels out selection bias is not supported. More generally, our results show that under relatively mild restrictions, we can obtain strong conclusions regarding our questions of interest.

School desegregation might have induced unintended behavioral responses of white families as well as state and local governments. This paper examines these responses and is the first to study the effects of desegregation on the finances of school districts. Desegregation induced white flight from blacker to whiter public school districts and to private schools, but the local property tax base and local revenue were not adversely affected. The state legislature directed significant new funding to districts where whites were particularly affected by desegregation. Desegregation therefore appears to have achieved its intended goal of improving resources available in schools that blacks attended.

Theory suggests that a firm facing competition will raise prices as consumer preferences become more diverse, and with high enough diversity, a duopolist under product differentiation may price higher than a monopolist. Focusing on the price for cable modem Internet access, with or without DSL competition, and using the standard deviation of education attainment as a proxy for preference diversity, we find empirical support for these results. In markets where cable competes with DSL, the cable Internet price increases with preference diversity. Moreover, the cable Internet price under DSL competition can exceed that without competition when preferences are sufficiently diverse.

U.S. firms' stock return volatility rose fivefold from 1971 through 2000 and then reverted to near 1971 levels by 2006. This was driven mainly by a rise and fall in the firm-specific, rather than systematic, component of volatility. Firm-level total factor productivity growth volatility exhibited a similar pattern. We hypothesize that firm heterogeneity, reflected in firm-specific volatility, rises as a new general purpose technology (GPT) propagates across the economy and then ebbs once the GPT is widespread. Measuring GPT adoption by information technology capital intensity, we find robust cross-industry empirical evidence supporting the hypothesis.

In this paper we provide new evidence on the impact on the U.S. CPI of the appearance and growth of new types of product outlets. Our CPI food microdata permit a more detailed categorization of outlet types than in previous studies, and we can adjust for numerous differences in item characteristics. We also examine the effects of changes in outlet mix not only across outlet categories but also within those categories. In our sample, we find that the upward impact on price from increased item quality has offset most, but not all, of the downward impact of lower-priced outlets.